Characterization of Hormone Receptor and HER2 Status in Breast Cancer Using Mass Spectrometry Imaging.

Immunohistochemical evaluation of estrogen receptor, progesterone receptor, and human epidermal growth factor receptor-2 status stratify the different subtypes of breast cancer and define the treatment course. Triple-negative breast cancer (TNBC), which does not register receptor overexpression, is often associated with worse patient prognosis. Mass spectrometry imaging transcribes the molecular content of tissue specimens without requiring additional tags or preliminary analysis of the samples, being therefore an excellent methodology for an unbiased determination of tissue constituents, in particular tumor markers. In this study, the proteomic content of 1191 human breast cancer samples was characterized by mass spectrometry imaging and the epithelial regions were employed to train and test machine-learning models to characterize the individual receptor status and to classify TNBC. The classification models presented yielded high accuracies for estrogen and progesterone receptors and over 95% accuracy for classification of TNBC. Analysis of the molecular features revealed that vimentin overexpression is associated with TNBC, supported by immunohistochemistry validation, revealing a new potential target for diagnosis and treatment.

Multicenter Evaluation of Tissue Classification by Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging.

Many studies have demonstrated that tissue phenotyping (tissue typing) based on mass spectrometric imaging data is possible; however, comprehensive studies assessing variation and classifier transferability are largely lacking. This study evaluated the generalization of tissue classification based on Matrix Assisted Laser Desorption/Ionization (MALDI) mass spectrometric imaging (MSI) across measurements performed at different sites. Sections of a tissue microarray (TMA) consisting of different formalin-fixed and paraffin-embedded (FFPE) human tissue samples from different tumor entities (leiomyoma, seminoma, mantle cell lymphoma, melanoma, breast cancer, and squamous cell carcinoma of the lung) were prepared and measured by MALDI-MSI at different sites using a standard protocol (SOP). Technical variation was deliberately introduced on two separate measurements via a different sample preparation protocol and a MALDI Time of Flight mass spectrometer that was not tuned to optimal performance. Using standard data preprocessing, a classification accuracy of 91.4% per pixel was achieved for intrasite classifications. When applying a leave-one-site-out cross-validation strategy, accuracy per pixel over sites was 78.6% for the SOP-compliant data sets and as low as 36.1% for the mistuned instrument data set. Data preprocessing designed to remove technical variation while retaining biological information substantially increased classification accuracy for all data sets with SOP-compliant data sets improved to 94.3%. In particular, classification accuracy of the mistuned instrument data set improved to 81.3% and from 67.0% to 87.8% per pixel for the non-SOP-compliant data set. We demonstrate that MALDI-MSI-based tissue classification is possible across sites when applying histological annotation and an optimized data preprocessing pipeline to improve generalization of classifications over technical variation and increasing overall robustness.

The added value of PSMA PET/MR radiomics for prostate cancer staging.

PURPOSE: To evaluate the performance of combined PET and multiparametric MRI (mpMRI) radiomics for the group-wise prediction of postsurgical Gleason scores (psGSs) in primary prostate cancer (PCa) patients. METHODS: Patients with PCa, who underwent [68 Ga]Ga-PSMA-11 PET/MRI followed by radical prostatectomy, were included in this retrospective analysis (n = 101). Patients were grouped by psGS in three categories: ISUP grades 1-3, ISUP grade 4, and ISUP grade 5. mpMRI images included T1-weighted, T2-weighted, and apparent diffusion coefficient (ADC) map. Whole-prostate segmentations were performed on each modality, and image biomarker standardization initiative (IBSI)-compliant radiomic features were extracted. Nine support vector machine (SVM) models were trained: four single-modality radiomic models (PET, T1w, T2w, ADC); three PET + MRI double-modality models (PET + T1w, PET + T2w, PET + ADC), and two baseline models (one with patient data, one image-based) for comparison. A sixfold stratified cross-validation was performed, and balanced accuracies (bAcc) of the predictions of the best-performing models were reported and compared through Student's t-tests. The predictions of the best-performing model were compared against biopsy GS (bGS). RESULTS: All radiomic models outperformed the baseline models. The best-performing (mean ± stdv [%]) single-modality model was the ADC model (76 ± 6%), although not significantly better (p > 0.05) than other single-modality models (T1w: 72 ± 3%, T2w: 73 ± 2%; PET: 75 ± 5%). The overall best-performing model combined PET + ADC radiomics (82 ± 5%). It significantly outperformed most other double-modality (PET + T1w: 74 ± 5%, p = 0.026; PET + T2w: 71 ± 4%, p = 0.003) and single-modality models (PET: p = 0.042; T1w: p = 0.002; T2w: p = 0.003), except the ADC-only model (p = 0.138). In this initial cohort, the PET + ADC model outperformed bGS overall (82.5% vs 72.4%) in the prediction of psGS. CONCLUSION: All single- and double-modality models outperformed the baseline models, showing their potential in the prediction of GS, even with an unbalanced cohort. The best-performing model included PET + ADC radiomics, suggesting a complementary value of PSMA-PET and ADC radiomics.

MALDI Mass Spectrometry Imaging for the Distinction of Adenocarcinomas of the Pancreas and Biliary Tree.

Pancreatic ductal adenocarcinoma and cholangiocarcinoma constitute two aggressive tumor types that originate from the epithelial lining of the excretory ducts of the pancreatobiliary tract. Given their close histomorphological resemblance, a correct diagnosis can be challenging and almost impossible without clinical information. In this study, we investigated whether mass spectrometric peptide features could be employed to distinguish pancreatic ductal adenocarcinoma from cholangiocarcinoma. Three tissue microarrays of formalin-fixed and paraffin-embedded material (FFPE) comprising 41 cases of pancreatic ductal adenocarcinoma and 41 cases of cholangiocarcinoma were analyzed by matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI). The derived peptide features and respective intensities were used to build different supervised classification algorithms: gradient boosting (GB), support vector machine (SVM), and k-nearest neighbors (KNN). On a pixel-by-pixel level, a classification accuracy of up to 95% could be achieved. The tentative identification of discriminative tryptic peptide signatures revealed proteins that are involved in the epigenetic regulation of the genome and tumor microenvironment. Despite their histomorphological similarities, mass spectrometry imaging represents an efficient and reliable approach for the distinction of PDAC from CC, offering a promising complementary or alternative approach to the existing tools used in diagnostics such as immunohistochemistry.

MALDI-MSI: A Powerful Approach to Understand Primary Pancreatic Ductal Adenocarcinoma and Metastases.

Cancer-related deaths are very commonly attributed to complications from metastases to neighboring as well as distant organs. Dissociate response in the treatment of pancreatic adenocarcinoma is one of the main causes of low treatment success and low survival rates. This behavior could not be explained by transcriptomics or genomics; however, differences in the composition at the protein level could be observed. We have characterized the proteomic composition of primary pancreatic adenocarcinoma and distant metastasis directly in human tissue samples, utilizing mass spectrometry imaging. The mass spectrometry data was used to train and validate machine learning models that could distinguish both tissue entities with an accuracy above 90%. Model validation on samples from another collection yielded a correct classification of both entities. Tentative identification of the discriminative molecular features showed that collagen fragments (COL1A1, COL1A2, and COL3A1) play a fundamental role in tumor development. From the analysis of the receiver operating characteristic, we could further advance some potential targets, such as histone and histone variations, that could provide a better understanding of tumor development, and consequently, more effective treatments.

Proteomics in Pathology.

Proteomic approaches are of growing importance in the biologist's toolbox. It greatly benefited from past and recent advances in sampling, chemical processing, mass spectrometry (MS) instrumentation, and data processing. MS-based analysis of proteins is now in the process of being translated in pathology for objective diagnoses. In this viewpoint, we present the workflows that we think are the most promising for applications in pathology. We also comment what we think are prerequisites for a successful translational implementation.

Interlaboratory concordance of PD-L1 immunohistochemistry for non-small-cell lung cancer.

AIMS: Programmed death ligand 1 (PD-L1) immunohistochemistry has become a mandatory diagnostic test in the treatment of lung cancer. Several research initiatives have started to harmonise the five PD-L1 immunohistochemistry assays that have been used in clinical trials. Here, we report data on interlaboratory and interassay concordance for commercial assays ('assays') and laboratory-developed tests (LDTs) at 10 German testing sites. METHODS AND RESULTS: To assess interlaboratory concordance, a tissue microarray containing 21 pulmonary carcinoma specimens was centrally prepared. Pre-cut sections were stained at 10 sites by the use of assays 28-8, 22C3, SP263, and SP142, as well as 11 LDTs. Assay performance was evaluated with a second tissue microarray containing 11 cell lines with defined PD-L1 expression. Quality control was centrally performed by manual and digital analyses. The assays yielded reproducible IHC staining patterns at all sites. In agreement with previous studies, 22C3, 28-8 and SP263 showed similar staining patterns, whereas SP142 was distinct. Among the LDTs, six of 11 protocols showed staining patterns similar to those of assays 22C3 and 28-8. Interlaboratory concordance of tumour cell scoring by use of a six-step system was moderate (Light's κ = 0.43-0.69), whereas the clinically approved cut-offs of ≥1% and ≥50% showed substantial concordance (κ = 0.73-0.89). Immune cell scoring by the use of SP142 yielded moderate concordance (κ = 0.42). CONCLUSIONS: The data confirm the previously described staining patterns of the assays, and show that they can be reproducibly employed at different sites. LDTs with staining results similar to those of the assays are implementable, but have to be carefully validated.

Reliable Entity Subtyping in Non-small Cell Lung Cancer by Matrix-assisted Laser Desorption/Ionization Imaging Mass Spectrometry on Formalin-fixed Paraffin-embedded Tissue Specimens.

Histopathological subtyping of non-small cell lung cancer (NSCLC) into adenocarcinoma (ADC), and squamous cell carcinoma (SqCC) is of utmost relevance for treatment stratification. However, current immunohistochemistry (IHC) based typing approaches on biopsies are imperfect, therefore novel analytical methods for reliable subtyping are needed. We analyzed formalin-fixed paraffin-embedded tissue cores of NSCLC by Matrix-assisted laser desorption/ionization (MALDI) imaging on tissue microarrays to identify and validate discriminating MALDI imaging profiles for NSCLC subtyping. 110 ADC and 98 SqCC were used to train a Linear Discriminant Analysis (LDA) model. Results were validated on a separate set of 58 ADC and 60 SqCC. Selected differentially expressed proteins were identified by tandem mass spectrometry and validated by IHC. The LDA classification model incorporated 339 m/z values. In the validation cohort, in 117 cases (99.1%) MALDI classification on tissue cores was in accordance with the pathological diagnosis made on resection specimen. Overall, three cases in the combined cohorts were discordant, after reevaluation two were initially misclassified by pathology whereas one was classified incorrectly by MALDI. Identification of differentially expressed peptides detected well-known IHC discriminators (CK5, CK7), but also less well known differentially expressed proteins (CK15, HSP27). In conclusion, MALDI imaging on NSCLC tissue cores as small biopsy equivalents is capable to discriminate lung ADC and SqCC with a very high accuracy. In addition, replacing multislide IHC by an one-slide MALDI approach may also save tissue for subsequent predictive molecular testing. We therefore advocate to pursue routine diagnostic implementation strategies for MALDI imaging in solid tumor typing.

MALDI imaging mass spectrometry - From bench to bedside.

Today, pathologists face many challenges in defining the precise morphomolecular diagnosis and in guiding clinicians to the optimal patients' treatment. To achieve this goal, increasingly, classical histomorphological methods have to be supplemented by high throughput molecular assays. Since MALDI imaging mass spectrometry (IMS) enables the assessment of spatial molecular arrangements in tissue sections, it goes far beyond microscopy in providing hundreds of different molecular images from a single scan without the need of target-specific reagents. Thus, this technology has the potential to uncover new markers for diagnostic purposes or markers that correlate with disease severity as well as prognosis and therapeutic response. Additionally, in the future MALDI IMS based classifiers measured with this technology in real time in the diagnostic setting might be applicable in the routine diagnostic setting. In this review, recently published studies that show the usefulness, advantages, and applicability of MALDI IMS in different fields of pathology (diagnosis, prognosis and treatment response) are highlighted. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann.

Value of 111 In-prostate-specific membrane antigen (PSMA)-radioguided surgery for salvage lymphadenectomy in recurrent prostate cancer: correlation with histopathology and clinical follow-up.

OBJECTIVES: To evaluate the use of 111 In-labelled prostate-specific membrane antigen (PSMA)-I&T-based radioguided surgery (111 In-PSMA-RGS) for salvage surgery in recurrent prostate cancer (PCa) using comparison of intra-operative gamma probe measurements with histopathological results of dissected specimens. In addition, to determine the success of 111 In-PSMA-RGS with regard to postoperative prostate-specific antigen (PSA) responses, PCa-specific treatment-free survival rates and postoperative complication rates. PATIENTS AND METHODS: A total of 31 consecutive patients with localized recurrent PCa undergoing salvage surgery with PSMA-targeted radioguided surgery using a 111 In-labelled PSMA ligand between April 2014 and July 2015 were retrospectively included in this study. The preoperative (interquartile range; range) median PSA level was 1.3 (0.57-2.53 ng/mL; 0.2-13.9 ng/mL). Results of ex vivo radioactivity rating (positive vs negative) of resected tissue specimens were compared with findings of postoperative histological analysis. Best PSA response without additional treatment was determined after 111 In-PSMA-RGS, and salvage-surgery-related postoperative complications and PCa-specific additional treatments were recorded. RESULTS: In 30/31 patients, 111 In-PSMA-RGS allowed intra-operative identification of metastatic lesions. In total, 145 surgical specimens were removed and 51 showed metastatic involvement at histological analysis. According to 111 In-PSMA-RGS ex vivo measurements, 48 specimens were correctly classified as metastatic and 87 as cancer-free, four were false-negative and six were false-positive compared with histological evaluation. Follow-up information was available for 30/31 patients. PSA declines of >50% and >90% were observed in 23/30 patients and in 16/30 patients, respectively. In 18/30 patients, a PSA decline to <0.2 ng/mL was observed. In 10/30 patients further PCa-specific treatment was given after a median (range) of 125 (48-454) days post-111 In-PSMA-RGS. The remaining 20 patients remained treatment-free at a median (range) follow-up of 337 (81-591) days. Of 30 patients, 10 presented with surgery-related complications (Clavien-Dindo grade 1, n = 6, Clavien-Dindo grade 3b, n = 4). CONCLUSION: 111 In-PSMA-RGS proved to be of high value for intra-operative detection of even small metastatic lesions in patients with PCa scheduled for salvage lymphadenectomy. It allows the exact localization and resection of metastatic tissue during 111 In-PSMA-RGS and is therefore anticipated to have a beneficial influence on further disease progression; however, identification of suitable patients on the basis of PSMA-positron-emission tomography imaging as well as clinical variables is essential for satisfactory results to be obtained.

Molecular Urothelial Tumor Cell Subtypes Remain Stable During Metastatic Evolution.

Urothelial cancer (UC) care is moving toward precision oncology. For tumor biology-driven treatment of metastatic UC (mUC), molecular subtypes play a crucial role. However, it is not known whether subtypes change during metastatic evolution. To address this, we analyzed a UC progression cohort (N = 154 patients) with 138 matched primary tumors (PRIM) and synchronous or metachronous distant metastasis (MET) by immunohistochemistry, and mRNA sequencing in a subgroup of 20 matched pairs. Protein-based tumor cell subtypes and histomorphology remained stable during metastatic progression (concordance: 94%, 95% confidence interval [CI] 88-97%). In comparison, transcriptome-based molecular consensus subtypes exhibited higher heterogeneity between PRIM and MET (concordance: 45%, 95% CI 23-69%), with switches particularly occurring between luminal and stroma-rich tumors. Of note, all tumors classified as stroma rich showed luminal tumor cell differentiation. By an in-depth analysis, we found a negative correlation of luminal gene and protein expression with increasing desmoplastic stroma content, suggesting that luminal tumor cell differentiation of "stroma-rich tumors" is superimposed by gene expression signals stemming from the stromal compartment. Immunohistochemistry allows tumor cell subtyping into luminal, basal, or neuroendocrine classes that remain stable during metastatic progression. These findings expand our biological understanding of UC MET and have implications for future subtype-stratified clinical trials in patients with mUC. PATIENT SUMMARY: Urothelial carcinomas (UCs) occur in different appearances, the so-called molecular subtypes. These molecular subtypes will gain importance for the therapy of metastatic UCs in the future. We could demonstrate that the subtype remains stable during metastasis, which is highly relevant for future studies.

Renal neuroendocrine tumors: clinical and molecular pathology with an emphasis on frequent association with ectopic Cushing syndrome.

Renal neuroendocrine tumors (RenNETs) are rare malignancies with largely unknown biology, hormone expression, and genetic abnormalities. This study aims to improve our understanding of the RenNETs with emphasis of functional, hormonal, and genetic features. Surgically resected RenNETs (N = 13) were retrieved, and immunohistochemistry and next-generation sequencing (NGS) were performed in all cases. In addition, all published RenNETs were systematically reviewed. Our cohort (4 men and 9 women, mean age 42, mean tumor size 7.6 cm) included 2 patients with Cushing syndrome (CS). WHO grade (23% G1, 54% G2, and 23% G3) and tumor progression did not correlate. CS-associated RenNETs (CS-RenNETs) showed a solid and eosinophilic histology and stained for ACTH, while the remaining non-functioning tumors had a trabecular pattern and expressed variably hormones somatostatin (91%), pancreatic polypeptide (63%), glucagon (54%), and serotonin (18%). The transcription factors ISL1 and SATB2 were expressed in all non-functioning, but not in CS-RenNETs. NGS revealed no pathogenic alterations or gene fusions. In the literature review (N = 194), 15 (8%) of the patients had hormonal syndromes, in which CS being the most frequent (7/15). Large tumor size and presence of metastasis were associated with shorter patients' survival (p < 0.01). RenNETs present as large tumors with metastases. CS-RenNETs differ through ACTH production and solid-eosinophilic histology from the non-functioning trabecular RenNETs that produce pancreas-related hormones and express ISL1 and SATB2. MEN1 or DAXX/ARTX abnormalities and fusion genes are not detected in RenNETs, indicating a distinct yet unknown molecular pathogenesis.

Heterogeneity of prostate-specific membrane antigen (PSMA) and PSMA-ligand uptake detection combining autoradiography and postoperative pathology in primary prostate cancer.

BACKGROUND: Targeting prostate-specific membrane antigen (PSMA) has been highly successful for imaging and treatment of prostate cancer. However, heterogeneity in immunohistochemistry indicates limitations in the effect of imaging and radionuclide therapy of multifocal disease. 99mTc-PSMA-I&S is a γ-emitting probe, which can be used for intraoperative lesion detection and postsurgical autoradiography (ARG). We aimed to study its intraprostatic distribution and compared it with (immuno)-histopathology. RESULTS: Seventeen patients who underwent RGS between 11/2018 and 01/2020 with a total of 4660 grids were included in the preliminary analysis. Marked intratumor and intra-patient heterogeneity of PSMA expression was detected, and PSMA negative foci were observed in all samples (100%). Heterogeneous intra-patient PSMA-ligand uptake was observed, and no significant correlation was present between the degree of heterogeneity of PSMA expression and PSMA-ligand uptake. Higher PSMA-ligand uptake was observed in GS ≥ 8 than GS < 8 (p < 0.001). The appearance of Gleason Pattern (GP) 4 was strongly associated with higher uptake (coefficient: 0.43, p < 0.001), while GP 5 also affected the uptake (coefficient: 0.07, p < 0.001). CONCLUSION: PSMA expression and PSMA-ligand uptake show marked heterogeneity. Prostate carcinoma with GP 4 showed significantly higher uptake compared with non-neoplastic prostate tissue. Our analyses extend the scope of applications of radiolabeled PSMA-ligands to ARG for identifying high-grade disease and using its signal as a noninvasive biomarker in prostate cancer.

Spatial Immunephenotypes of Distant Metastases but not Matched Primary Urothelial Carcinomas Predict Response to Immune Checkpoint Inhibition.

BACKGROUND: The value of programmed cell death ligand-1 (PD-L1) to predict durable responses to immune checkpoint inhibitors (ICIs) in metastatic urothelial carcinoma (mUC) is inconsistent. We hypothesize that the use of archived primary tumor material (PRIM) for PD-L1 testing in clinical trials not properly reflecting the metastatic disease status (MET) contributes to this clinical issue. OBJECTIVE: To analyze the predictive and prognostic value of PD-L1, spatial immunephenotypes, and major histocompatibility complex class I (MHC-I) determined in patient-matched PRIM/MET. DESIGN, SETTING, AND PARTICIPANTS: PD-L1, spatial immunephenotypes, and MHC-I were examined in 154 mUC patients with at least one available pretreatment MET (138 patient-matched PRIM/MET pairs). OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: PD-L1, spatial immunephenotype, and MHC-I status of (patient-matched PRIM and) pretreatment MET were correlated with chemotherapy and ICI response and outcomes. RESULTS AND LIMITATIONS: Discordance rates in patient-matched PRIM/MET were 25/30%, 36%, and 49% for PD-L1 (CPS10/IC5%), immunephenotypes, and MHC-I (loss vs preserved), respectively. Correlations with chemotherapy and ICI responses were observed for immunephenotypes and MHC-I status determined in MET (not for PD-L1 alone), but not in PRIM. In case of ICIs, patients with cytotoxic tumor immune microenvironment (TIME) showed durable responses with disease control rates of 90% and a hazard ratio for disease progression/death of 0.05 (95% confidence interval: 0.01-0.65) versus patients with immunedepleted MET (disease control rate 29%). MET MHC-I status added an incremental value to predict durable ICI responses. Limitations include the partly retrospective design and the lack of MET multisampling on individual patient level. CONCLUSIONS: The TIME is subject to substantial dynamics during metastatic evolution. MET immunephenotypes and MHC-I statuses show promising potential to predict chemotherapy and durable ICI responses, while the PRIM TIME does not. Thus, future clinical trials should rather rely on pretreatment MET biopsies reflecting the current immunological disease state than on PRIM. PATIENT SUMMARY: Prediction of chemotherapy and responses to immune checkpoint inhibitors might be possible using representative pretreatment metastatic biopsies.

Membranous NECTIN-4 Expression Frequently Decreases during Metastatic Spread of Urothelial Carcinoma and Is Associated with Enfortumab Vedotin Resistance.

PURPOSE: The antibody-drug conjugate enfortumab vedotin (EV) releases a cytotoxic agent into tumor cells via binding to the membrane receptor NECTIN-4. EV was recently approved for patients with metastatic urothelial carcinoma (mUC) without prior assessment of the tumor receptor status as ubiquitous NECTIN-4 expression is assumed. Our objective was to determine the prevalence of membranous NECTIN-4 protein expression in primary tumors (PRIM) and patient-matched distant metastases (MET). EXPERIMENTAL DESIGN: Membranous NECTIN-4 protein expression was measured (H-score) by IHC in PRIM and corresponding MET (N = 137) and in a multicenter EV-treated cohort (N = 47). Progression-free survival (PFS) after initiation of EV treatment was assessed for the NECTIN-4-negative/weak (H-score 0-99) versus moderate/strong (H-score 100-300) subgroup. The specificity of the NECTIN-4 IHC staining protocol was validated by establishing CRISPR-Cas9-induced polyclonal NECTIN-4 knockouts. RESULTS: In our cohort, membranous NECTIN-4 expression significantly decreased during metastatic spread (Wilcoxon matched pairs P < 0.001; median H-score = 40; interquartile range, 0-140), with 39.4% of MET lacking membranous NECTIN-4 expression. In our multicenter EV cohort, absence or weak membranous NECTIN-4 expression (34.0% of the cohort) was associated with a significantly shortened PFS on EV (log-rank P < 0.001). CONCLUSIONS: Membranous NECTIN-4 expression is frequently decreased or absent in mUC tissue. Of note, the clinical benefit of EV strongly depends on membranous NECTIN-4 expression. Thus, our results are of highest clinical relevance and argue for a critical reconsideration of the current practice and suggest that the NECTIN-4 receptor status should be determined (ideally in a metastatic/progressive lesion) before initiation of EV. See related commentary by Aggen et al., p. 1377.

Imaging of intact tissue sections: moving beyond the microscope.

MALDI-imaging MS is a new molecular imaging technology for direct in situ analysis of thin tissue sections. Multiple analytes can be monitored simultaneously without prior knowledge of their identities and without the need for target-specific reagents such as antibodies. Imaging MS provides important insights into biological processes because the native distributions of molecules are minimally disturbed, and histological features remain intact throughout the analysis. A wide variety of molecules can be imaged, including proteins, peptides, lipids, drugs, and metabolites. Several specific examples are presented to highlight the utility of the technology.

Mass Spectrometry Imaging Spatial Tissue Analysis toward Personalized Medicine.

Novel profiling methodologies are redefining the diagnostic capabilities and therapeutic approaches towards more precise and personalized healthcare. Complementary information can be obtained from different omic approaches in combination with the traditional macro- and microscopic analysis of the tissue, providing a more complete assessment of the disease. Mass spectrometry imaging, as a tissue typing approach, provides information on the molecular level directly measured from the tissue. Lipids, metabolites, glycans, and proteins can be used for better understanding imbalances in the DNA to RNA to protein translation, which leads to aberrant cellular behavior. Several studies have explored the capabilities of this technology to be applied to tumor subtyping, patient prognosis, and tissue profiling for intraoperative tissue evaluation. In the future, intercenter studies may provide the needed confirmation on the reproducibility, robustness, and applicability of the developed classification models for tissue characterization to assist in disease management.

Prevalence of Castleman's disease in patients suffering from cervical lymphadenopathy.

Objectives: To determine the prevalence of Castleman's disease (unicentric/idiopathic multicentric CD) in a retrospective cohort according to the newly defined international diagnostic criteria in patients, who underwent a lymph node removal at a tertiary care university hospital over a period of 10 years. Study design: Retrospective chart review. Material and methods: All Patients with cervical lymphadenopathy coded by ICD-10-CM with "I88.9," "R59.0," or "D47.Z2" between January 2010 and December 2020 and who underwent a lymph node extirpation were identified. In cases who met the diagnostic criteria for a potential unicentric or idiopathic multicentric CD (iMCD) diagnosis, the lymph node tissue was re-evaluated by a pathologist. Results: A total of 714 patients with cervical lymphadenopathy were included into this single-center retrospective study. After exclusion of patients with diseases that may mimic iMCD and cases for which material to perform histological re-evaluation was lacking, a subset of 75 patients with "nonspecific lymphadenitis" or "reactive hyperplasia of lymph node" was identified, who underwent a renewed histopathological examination. One case fulfilled both the major and minor criteria of an iMCD diagnosis, and further 15 cases matched the histological criterion of an iMCD diagnosis (one of the two major diagnostic criteria), so that a UCD diagnosis according to the new criteria could be accepted. Conclusion: In this cohort, the subsequent application of the new diagnostic criteria led to further cases of CD (1.9% compared to 0.1% before) being recognized. Although incidence and prevalence of UCD and iMCD are low, clinicians should keep in mind this differential diagnosis as effective therapies are available. Level of Evidence: 4.

Validation of 18F-rhPSMA-7 and 18F-rhPSMA-7.3 PET Imaging Results with Histopathology from Salvage Surgery in Patients with Biochemical Recurrence of Prostate Cancer.

18F-rhPSMA-7, and its single diastereoisomer form, 18F-rhPSMA-7.3, are prostate-specific membrane antigen (PSMA)-targeting radiopharmaceuticals. Here, we investigated their accuracy for the assessment of lymph node (LN) metastases validated by histopathology. Methods: Data from 58 patients with biochemical recurrence of prostate cancer after radical prostatectomy receiving salvage surgery after PET imaging with 18F-rhPSMA-7 or 18F-rhPSMA-7.3 were retrospectively reviewed. Two nuclear medicine physicians reviewed all PET scans and morphologic imaging in consensus. Readers were masked from the results of histopathology. PET and morphologic imaging were correlated with histopathology from resected LNs. Results: In 75 of 150 resected regions in 54 of 58 patients, tumor lesions were present in histopathology. The template-based specificity of PET (18F-rhPSMA-7 and 18F-rhPSMA-7.3 combined) and morphologic imaging was 93.3% and 100%, respectively. However, 18F-rhPSMA-7 and 18F-rhPSMA-7.3 PET detected metastases in 61 of 75 histopathologically proven metastatic LN fields (81.3%) whereas morphologic imaging was positive in only 9 of 75 (12.0%). The positive predictive value was 92.4% for 18F-rhPSMA-7 and 18F-rhPSMA-7.3 PET and 100% for morphologic imaging. 18F-rhPSMA-7 and 18F-rhPSMA-7.3 PET performance was significantly superior to morphologic imaging (difference in the areas under the receiver-operating-characteristic curves, 0.222; 95% CI, 0.147-0.298; P < 0.001). The mean size of PET-positive and histologically confirmed LN metastases was 6.3 ± 3.1 mm (range, 2-15 mm) compared with a mean size of 9.8 ± 2.5 mm (range, 7-15 mm) on morphologic imaging. Conclusion: 18F-rhPSMA-7 and 18F-rhPSMA-7.3 PET offer a high positive predictive value comparable to that reported for 68Ga-PSMA-11 and represent a valuable tool for guiding salvage lymphadenectomy.